A cross-sectional questionnaire study: Impaired awareness of hypoglycaemia remains prevalent in adults with type 1 diabetes and is associated with the risk of severe hypoglycaemia

Objective Impaired awareness of hypoglycaemia (IAH) is a risk factor for severe hypoglycaemia (SH) in type 1 diabetes (T1D). Much of the IAH prevalence data comes from older studies where participants did not have the benefit of the latest insulins and technologies. This study surveyed the prevalence of IAH and SH in a tertiary adult clinic population and investigated the associated factors. Methods Adults (≥18 years) attending a tertiary T1D clinic completed a questionnaire, including a Gold and Clarke score. Background information was collected from health records. Results 189 people (56.1% female) with T1D (median [IQR] disease duration 19.3 [11.5, 29.1] years and age of 41.0 [29.0, 52.0] years) participated. 17.5% had IAH and 16.0% reported ≥1 episode of SH in the previous 12 months. Those with IAH were more likely to report SH (37.5% versus 11.7%, p = 0.001) a greater number of SH episodes per person (median [IQR] 0 [0,2] versus 0 [0,0] P<0.001) and be female (72.7% versus 52.6%, p = 0.036). Socio-economic deprivation was associated with IAH (p = 0.032) and SH (p = 0.005). Use of technology was the same between IAH vs aware groups, however, participants reporting SH were more likely to use multiple daily injections (p = 0.026). Higher detectable C-peptide concentrations were associated with a reduced risk of SH (p = 0.04). Conclusion Insulin pump and continuous glucose monitor use was comparable in IAH versus aware groups. Despite this, IAH remains a risk factor for SH and is prevalent in females and in older people. Socioeconomic deprivation was associated with IAH and SH, making this an important population to target for interventions.


Introduction
Type 1 diabetes (T1D) affects ~35,000 people in Scotland [1].It is characterised by autoimmune destruction of the pancreatic beta cells leading, in time, to absolute or near absolute insulin deficiency [2].T1D is mainly managed with insulin replacement therapy which is given by multiple daily subcutaneous injections or continuous subcutaneous insulin infusion (CSII).
The landmark Diabetes Control and Complications (DCCT) trial found that the use of intensive insulin therapy in T1D reduced the risk of long-term microvascular complications, but that intensive therapy also increased the risk of hypoglycaemia [3].A recent prospective study identified hypoglycaemia as an ongoing burden for people with T1D who experience on average 73.3 hypoglycaemic events/patient-year [4].This effect is due in part to the inability of exogenous insulin to mimic the normal profile of endogenous insulin production, leading to relative insulin excess at inappropriate times [2], impairment of the normal compensatory hormone responses to lower blood glucose [5] and the loss of behavioural responses due to IAH [2] which affects 20-40% of people with T1D [6,7].IAH is a risk factor for SH [8], defined as an episode of hypoglycaemia requiring external assistance for recovery.IAH increases the risk of a SH event 6-fold [6,9].
People with T1D can regain hypoglycaemia awareness through avoidance of hypoglycaemia [2,[10][11][12].Diabetes technologies such as continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) can reduce overall episodes of hypoglycaemia [13,14], improve glycaemic control and decrease the risk of microvascular complications [15].Advanced diabetes technologies, such as hybrid closed-loop systems, have been shown to reduce time in hypoglycaemia both in randomised controlled trials (RCTs) [16][17][18][19] and in real-world studies [20].However, their impact on IAH is not clear due to exclusion of participants with IAH from some RCTs [17] and other trials not reporting data on IAH [18].Additional studies investigating the effect of HCL systems on the counterregulatory response to hypoglycaemia and IAH in T1D are required [21] to further evaluate the possible benefits of these devices for those at risk of hypoglycaemia.
Technologies currently available in our clinic are: intermittently scanned CGM (isCGM), which users need to interact with in order to see their glucose data; real-time CGM (rtCGM) which transfers data in real-time to the user and CSII which can be used as part of a non-integrated system or as part of a hybrid closed-loop (HCL) system where there is automatic adjustment of insulin delivery based on readings from a rtCGM device.We surveyed an unselected population of adults with T1D to investigate associations between SH and IAH prevalence and the use of technology.Health records of respondents were then screened to identify factors associated with IAH and SH.

Participants
Between the 1 st of July 2021 and the 31 st of August 2022 adults (�18 years) attending a tertiary hospital T1D clinic in person were approached to complete the study survey.People with a diagnosis of T1D documented in their health record and a length of diagnosis of �2 years were considered eligible.Those unable to understand or complete the survey were excluded.The study was approved by the local research and development office (2021/0092) and research ethics committee (21/WA/0149).Written informed consent was obtained from participants.

Questionnaire
The first part of the questionnaire included a Gold [9] and Clarke [22] Score.Both are validated methods for assessing hypoglycaemia awareness in people with T1D [23].In brief, for the Gold Score the participant is asked 'Do you know when your hypos are commencing?'.They respond using a 7-point Likert scale with 1 indicating 'always aware' and 7 indicating 'never aware'.A score of �4 represents IAH.The Clarke score comprises 8 questions that assess exposure to moderate and severe hypoglycaemia as well as assessing the glucose level for onset of symptoms.It gives a score of 0-8 with a score of �4 representing IAH.
The second part of the questionnaire collected additional information on employment status, education level, time off work or education due to hypoglycaemia, history of SH in the previous 12 months, driving status and use of diabetes technology.

Additional data
Participant health records were reviewed to collect background information and demographic details including age, sex, age at diagnosis, HbA1c, insulin, date commenced CSII if applicable, date commenced intermittently scanned CGM (isCGM) or real time CGM (rtCGM) if applicable, postcode and hospital admissions in the previous 12 months related to diabetes.Socioeconomic status was assessed using the Scottish index for multiple deprivation (SIMD) quintile [24].C-peptide data was also collected from participant's health records.Participant's using an isCGM had a 2-week snapshot of their data collected from Libreview consisting of: time in range (TIR) 3.9-10 mmol/L, time below range (TBR) <3.9 mmol/L, time above range (TAR) >10 mmol/L, average glucose, standard deviation (SD) of glucose and coefficient of variation (CV) of glucose.We did not collect information on the alarm functionality of the isCGM used.

C-peptide analysis
C-peptide samples obtained prior to October 2021 were analysed by Abbot Architect and after this by Roche Elecsys.Values are reported down to the limit of detection, 3pmol/L for the Abbot system and 7pmol/L for the Roche system.Results below this limit of detection are reported as 0 pmol/L in this paper.Random C-peptide levels were ascertained from medical records.

Statistical analysis
Results are reported as median (IQR) unless otherwise specified.Group differences in continuous variables were compared either using the unpaired t-test or Mann-Whitney U Test. Categorical variables were compared using the chi-square test.Logistic regression models were constructed with presence / absence of SH as the dependent variable and IAH as the independent variable.In order to explore if CSII affected the relationship between the variables, CSII was next added to the model and the relationship between the variables examined and the regression coefficients (beta co-efficients) for standardised data compared.
A p-value of <0.05 was considered significant.Statistical analysis was completed using IBM SPSS version 25.Data analysis was performed using Graph Pad Prism version 9 (Boston, USA).

Results
189 participants (56.1% female) completed the survey, IAH was defined as a Gold Score �4, or where this was missing (2.1%), a Clarke score �4.The prevalence of IAH was 17.5%.Of note the prevalence of IAH was 17.5% using either score.When analysing respondents who completed both the Gold and Clarke questionnaires (93.1%), there was a significant positive correlation between the two scores, Pearson r 0.623 (P<0.001).15.9% of respondents reported an episode of SH in the previous 12 months with a median (IQR) 0 (0,0) (range 0-12) number of episodes per person.The Gold and Clarke Score were discordant in 16 of 189 cases and 3 of the 16 had experienced SH in the preceding 12 months, but no further statistical analyses were possible due to the small numbers.The median (IQR) HbA1c was 60.0 (51.0, 67.0) mmol/mol (7.6 [6.8, 8.3]%).56.6% of respondents were using multiple daily injections (MDI).70.4% of respondents were using first generation insulin analogues as their bolus insulin and, of those using a basal insulin, 62.6% were using a second-generation analogue.The most common glucose monitoring method was isCGM with 81.0% of respondents using this.Of the 11.1% who were rtCGM users, 52.4% were using an unlicenced do-it-yourself (DIY) isCGM add-on to convert the device to a rtCGM sensor.Of the respondents using CSII, 9.8% were using hybrid closed loop (HCL) systems with 25% of these being a DIY HCL system.
72.7% of participants held a UK driving licence with 4.7% having previously surrendered their licence.While it did not reach statistical significance a numerically higher percentage of male respondents were drivers (77.1% versus 69.5%) and held a category of licence other than for driving a car alone (19.0%versus 12.7%).
Overall population characteristics are summarised in Table 1.
IAH was associated with socioeconomic deprivation, 60.6% of respondents with IAH were in Scottish index of multiple deprivation (SIMD) quintile 1 to 3 compared to 39.4% of respondents with normal awareness (p = 0.032) (Fig 2).Analysing the proportion of IAH in the different SIMD categories by chi-squared analysis demonstrated a difference between the 5 socioeconomic quintiles (p = 0.01).
Numerically a higher percentage of people with IAH had a diabetes-related hospital admission in the previous 12 months, 18.2% vs. 8.3%, but this did not reach statistical significance (p = 0.087).There was also a trend for people with IAH being diagnosed at an older age with a median (IQR) age at diagnosis of 20 (10.0, 37.5) years versus 16.0 (10.2, 25.0) years (p = 0.092).The proportions of people with IAH were compared between all 5 SIMD quintiles by chisquared testing.The quintiles were amalgamated into low and high socioeconomic categories using SIMD 1-3 (low socioeconomic status) and SIMD 4-5 (high socioeconomic status).
SH was associated with socioeconomic deprivation.Those reporting an episode of SH were more likely to be unemployed, 26.7% compared to 6.5% (p = 0.036), and to come from the most deprived SIMD quintiles, 66.7% compared to 38.1% (p = 0.005).
People with a history of SH were more likely to be MDI users, 76.7% compared to 53.2% (p = 0.026).There was no group difference in the method for monitoring blood glucose with the majority using isCGM in both the SH group and the group with no history of SH, 73.3% and 82.2% respectively (p = 0.164).

Discussion
In this cross-sectional survey study completed by 189 adults with T1D the prevalence of IAH was 17.4%.This is similar to a Norwegian study by Olsen et al in 2014 which also found a prevalence of IAH of 17% [25] and implies that the prevalence of IAH has not changed in almost 10 years despite advances in technology.It is, however, a slightly lower rate than reported in a previous study from our centre, which surveyed 518 people with T1D and identified IAH in 19.5% of respondents [6].However, the population characteristics between this study and ours are different.The previous study's population was younger at the time of completing the survey, median (IQR) age 39 (31-50) years; had a shorter time since diagnosis, 16 (9-24) years and had a higher mean (SD) HbA1c, 68.3 (15.3) mmol/mol (8.4 [1.4]%).Diabetes management amongst respondents in the previous study was also different with no respondents using CSII.This may limit the comparability of these studies.Another recent cross-sectional survey study investigated SH and IAH in CGM users [26].This survey cohort had high levels of technology use, 80% were CSII users and 61% HCL users.Despite this they report higher levels of SH and IAH in their cohort, 33% had a Gold score �4 and 34.6% had experienced an episode of SH.It may be that a higher proportion of people in their cohort with IAH or a history of SH were on more advanced technologies as a result of these problems.In our study, the rate of SH was greater in the IAH vs aware group despite equal access to CGM technology.However, it is possible that the IAH group, after adoption of CGM experienced an absolute decrease in the rate of SH, but our study was not set up to examine longitudinal changes within individual groups.Furthermore, it highlights the importance of these high-risk populations being included in future studies of these devices to assess the impact.Similar to our study, this survey found those with a history of SH had higher HbA1c and average glucose levels.A recent cross-sectional study among 509 individuals from the Netherlands with T1D, which used the Clarke score for assessment of IAH and SH, showed an overall prevalence of IAH of 15%, the lower prevalence of IAH compared to our study may be explained by a relatively young study population (median 32 years).It showed that participants with IAH were older, had longer diabetes duration and, interestingly, https://doi.org/10.1371/journal.pone.0297601.g003a higher age of diabetes onset and a greater proportion of those with IAH versus those that had awareness, were on glucose sensors.The study demonstrated that residual C-peptide secretion was protective, both for IAH and for SH, and that IAH was associated with a nine times higher risk of SH in the preceding year [27].Our study showed comparable rates of IAH to this, but the C-peptide levels were similar between the IAH and hypoglycaemic aware group; We did see a reduced incidence of SH in those with higher detectable C-peptide concentrations as has been reported previously [28] demonstrating the benefit of even very low levels of C-peptide concentrations against hypoglycaemia concordant with studies in islet transplant recipients [29].Some of the residual C-peptide levels in this reported study were much greater than in our study and overall the range of C-peptide concentrations were greater which may have accounted for the differences between the two studies.In the Netherlands individuals with T1D and IAH are eligible for both the prescription and the reimbursement of real-time glucose monitoring and use of a glucose sensor is probably a consequence of, and not a risk factor for, IAH [27].
In our study, those reporting IAH were 4 times more likely to report at least 1 episode of SH in the previous 12 months, which is concordant with other studies demonstrating an association between IAH and SH [30].SH is linked to morbidity, mortality and reduced quality of life (QoL), making it an important target for interventions in people with T1D.While there was no difference in the type of insulin or technology used in the IAH subgroups, we did identify that those using MDI were almost 3-times more likely to have had an episode of SH in the previous 12 months, and that MDI use was most in the most deprived quintile.The data supporting a positive impact of diabetes technology on IAH is scant.A recent paper suggested CGM has reduced the prevalence of IAH, though this premise has been challenged [31].Many studies of insulin technologies do not include people who are at risk of hypoglycaemia, that is, people with a history of SH or IAH, and so it can be difficult to comment on the impact of these devices on the risk of IAH.The lack of representation of these patient cohorts in research studies investigating these devices is a problem.One of the few studies to show improvement in IAH [32] (30) found that diabetes education was key, with no difference between technology groups.The authors acknowledge that the use of the most advanced technologies, such as HCL systems and rtCGM was low in our study, however, this is representative of our local T1D clinic population as reimbursement for isCGM is standard.We did identify a significantly higher proportion of people with normal awareness using a DIY rtCGM system than those with IAH.This is likely due to IAH being a criterion for receiving funded rtCGM in our clinic.Locally, IAH and SH are criteria for referral for more advanced diabetes technologies, however, this work highlights the need to assess patients who are not able to attend clinic using other modalities.It is this sort of data that can influence policy, improve community outreach and aid the development of strategies to help inform and improve access to technology, which may improve uptake and engagement in those difficult to reach lower socioeconomic groups.Such strategies may include reducing barriers to access technologies by offering these to all, increasing provision of information out with the hospital setting and, importantly, peer support.IAH and a history of SH was associated with the most deprived SIMD quintiles.Health disparities exist in T1D (27,30,31]) and previous studies have reported an increased risk of SH in people from more deprived socioeconomic backgrounds [31].However, few studies have linked IAH with socioeconomic status as reported here.Only 5.7% of all respondents in this study were from the most deprived SIMD quintile (quintile 1) and 56.8% were from the least deprived quintiles (quintile 4 and 5).This means that the prevalence of IAH and SH in people from the most socioeconomically deprived areas is likely underestimated in this study.The low proportion of people from the most deprived areas completing this study may in part be due to the questionnaire being administered at a face-to-face clinic: people from the most deprived socioeconomic backgrounds often face more barriers to engaging with health appointments and so the population we have surveyed is not likely to be fully representative of this group.Previous studies, indicate that non-attenders may have poorer glycaemic control [33] and conceivably higher rates of SH and IAH.As we do not have ethical permission to collect data from non-attenders, we may have underestimated the prevalence of both SH and IAH in the general clinic population.In the IAH group there was a higher proportion of female respondents compared to males, 72.7% versus 52.2%.This may be skewed by the higher proportion of female respondents in the study, 55.7%.This is not a pattern that has been previously reported in studies investigating IAH.Of note IAH was more prevalent in older people and in females.It is recognised that SH is more prevalent in women during pregnancy.We hypothesise that in this population of women their exposure to SH may have been greater due to tight glycaemic control in pregnancy with a subsequent increase in prevalence of IAH in later years as compared to the males.However further studies are required.
We do not have information regarding renal function in patients.Renal failure is a major risk factor for SH and low eGFR is associated with IAH (27).However, intervention with diabetes technology may still positively impact this group and this could be the basis for future work.
Data from experimental studies suggest a link between neuropathy and/or cardiovascular disease and hypoglycaemic episodes in T1D [34].The prevalence of other diabetes related complications might affect hypoglycaemia risk and outcomes, and this could also be included in future work.
As previously noted, a higher proportion of male respondents held a driving licence and a category of licence other than for driving a car alone.Some of these respondents may have had these licence categories as part of their job, which may have made them less forthcoming about their hypoglycaemia awareness status.Contrary to previous studies C-peptide levels in this patient cohort were not associated with CGM glycaemic metrics such as average glucose, TBR and TAR [35,36].However, in these studies C-peptide levels were higher.We did not demonstrate an association between C-peptide and HbA1c in our sample.A previous study investigating the impact of random C-peptide on risk of complications and glycaemic control found a lower HbA1c in participants with a C-peptide >200pmol/L [37].
This study does have limitations: It was carried out during Covid 19 pandemic restrictions so face-to-face clinic appointment numbers were lower than usual.This study may not necessarily be representative of the wider T1D population as people attending the clinic are more likely to be compliant with treatment and prepared to embrace new technologies versus those who do not attend.Also, older people were more likely to complete our survey, which meant that there were few participants with short duration T1D.A further limitation was that the study was completed as a one-off survey and so relied on the recall of participants at a single point in time, however, recall of SH events in the previous 12 months has been shown to be robust [38].This also means that we do not have information about the hypoglycaemia awareness status or history of SH in respondents before they started using diabetes technologies.The survey was carried out at a single site and only included participants attending a face-toface clinic.This may have selected out more motivated and possibly a better controlled cohort than the general clinic population.It is important for future studies to reach a wider general clinic population, so that the true extent of these problems can be assessed, and management plans instigated to prevent associated morbidity and mortality.

Conclusions
IAH remains a problem for people living with T1D, with a prevalence rate of 17.4% in this study.In our cohort IAH was associated with a 4-fold increased risk of SH.Both IAH and SH were more prevalent in females and those from a more deprived socioeconomic background and respondents with these problems were more likely to be unemployed.Our study did not identify any difference in the use of diabetes technologies between groups in those who were aware vs those with IAH.However, SH was lower in those using technology.
As has been demonstrated in other studies detectable C-peptide concentrations even at very low levels are protective against SH.Similar to real-world observational studies we found that IAH and SH are associated with higher HbA1c and average glucose levels.
Randomised controlled trials are required to investigate if and how advanced diabetes technologies are beneficial for participants with IAH and, or a history of SH.Since IAH and SH were more prevalent in the most socioeconomic deprived areas, it is important that participants are actively recruited from these groups.

Fig 1 .
Fig 1. A. Respondents reporting severe hypoglycaemia in the previous 12 months.Percentage of participants reporting at least one episode of SH in the preceding 12 months categorised by normal vs impaired awareness of hypoglycaemia.B. Number of severe hypoglycaemia events per patient in the previous 12 months.Number of episodes of SH per participant in the preceding 12 months, categorised by normal vs impaired awareness of hypoglycaemia.(Interquartile and absolute ranges shown by violin plot).https://doi.org/10.1371/journal.pone.0297601.g001

Fig 3 .
Fig 3. History of severe hypoglycaemia in the past 12 months and random C-peptide level.Random C-peptide levels in participants with �1SH vs. none in the preceding 12 months.C peptide levels between the groups was statistically significant.